针对当前算力网络安全服务发展中存在的资源池编排调度效率低下、云网安技术融合不足等关键问题,以运营商在安全服务市场面临的云网安协同创新与运营压力为研究背景,提出基于IPv6转发平面的段路由(segment routing over IPv6,SRv6)+应...针对当前算力网络安全服务发展中存在的资源池编排调度效率低下、云网安技术融合不足等关键问题,以运营商在安全服务市场面临的云网安协同创新与运营压力为研究背景,提出基于IPv6转发平面的段路由(segment routing over IPv6,SRv6)+应用响应网络(application responsive network,ARN)的算力网络安全排调度技术策略。该策略通过深度融合SRv6协议实现网络与业务端到端贯通,运用ARN提升数据面标识的简洁性和动态调度能力,构建具备高效编排调度能力的网络数据平面,支持安全业务的灵活组合和快速部署。研究成果主要包含SRv6+ARN编排调度技术架构、关键技术和可靠性保障,为运营商构建云网安协同的算力网络安全资源池提供技术支撑。展开更多
Remote sensing technologies play a vital role in our understanding of earthquakes and their impact on the Earth's surface.These technologies,including satellite imagery,aerial surveys,and advanced sensors,contribu...Remote sensing technologies play a vital role in our understanding of earthquakes and their impact on the Earth's surface.These technologies,including satellite imagery,aerial surveys,and advanced sensors,contribute significantly to our understanding of the complex nature of earthquakes.This review highlights the advancements in the integration of remote sensing technologies into earthquake studies.The combined use of satellite imagery and aerial photography in conjunction with geographic information systems(GIS)has been instrumental in showcasing the significance of fusing various types of satеllitеdata sourcеs for comprеhеnsivееarthquakеdamagеassеssmеnts.However,remote sensing encounters challenges due to limited pre-event imagery and restricted postearthquake site access.Furthеrmorе,thеapplication of dееp-lеarning mеthods in assеssingеarthquakе-damagеd buildings dеmonstratеs potеntial for furthеr progrеss in this fiеld.Overall,the utilization of remote sensing technologies has greatly enhanced our comprehension of earthquakes and their effects on the Earth's surface.The fusion of remote sensing technology with advanced data analysis methods holds tremendous potential for driving progress in earthquake studies and damage assessment.展开更多
The prompt detection and proper evaluation of necrotic retinal region are especially important for the diagnosis and treatment of acute retinal necrosis(ARN).The potential application of artificial intelligence(AI)alg...The prompt detection and proper evaluation of necrotic retinal region are especially important for the diagnosis and treatment of acute retinal necrosis(ARN).The potential application of artificial intelligence(AI)algorithms in these areas of clinical research has not been reported previously.The present study aims to create a computational algorithm for the automated detection and evaluation of retinal necrosis from retinal fundus photographs.A total of 149 wide-angle fundus photographs from40 eyes of 32 ARN patients were collected,and the U-Net method was used to construct the AI algorithm.Thereby,a novel algorithm based on deep machine learning in detection and evaluation of retinal necrosis was constructed for the first time.This algorithm had an area under the receiver operating curve of 0.92,with 86%sensitivity and 88%specificity in the detection of retinal necrosis.For the purpose of retinal necrosis evaluation,necrotic areas calculated by the AI algorithm were significantly positively correlated with viral load in aqueous humor samples(R2=0.7444,P<0.0001)and therapeutic response of ARN(R2=0.999,P<0.0001).Therefore,our AI algorithm has a potential application in the clinical aided diagnosis of ARN,evaluation of ARN severity,and treatment response monitoring.展开更多
基金funded through an appointment with the Agricultural Research Service,managed by the Oak Ridge Institute for Science and Education。
文摘Remote sensing technologies play a vital role in our understanding of earthquakes and their impact on the Earth's surface.These technologies,including satellite imagery,aerial surveys,and advanced sensors,contribute significantly to our understanding of the complex nature of earthquakes.This review highlights the advancements in the integration of remote sensing technologies into earthquake studies.The combined use of satellite imagery and aerial photography in conjunction with geographic information systems(GIS)has been instrumental in showcasing the significance of fusing various types of satеllitеdata sourcеs for comprеhеnsivееarthquakеdamagеassеssmеnts.However,remote sensing encounters challenges due to limited pre-event imagery and restricted postearthquake site access.Furthеrmorе,thеapplication of dееp-lеarning mеthods in assеssingеarthquakе-damagеd buildings dеmonstratеs potеntial for furthеr progrеss in this fiеld.Overall,the utilization of remote sensing technologies has greatly enhanced our comprehension of earthquakes and their effects on the Earth's surface.The fusion of remote sensing technology with advanced data analysis methods holds tremendous potential for driving progress in earthquake studies and damage assessment.
基金the National Natural Science Foundation of China(Nos.81870648 and 82070949)。
文摘The prompt detection and proper evaluation of necrotic retinal region are especially important for the diagnosis and treatment of acute retinal necrosis(ARN).The potential application of artificial intelligence(AI)algorithms in these areas of clinical research has not been reported previously.The present study aims to create a computational algorithm for the automated detection and evaluation of retinal necrosis from retinal fundus photographs.A total of 149 wide-angle fundus photographs from40 eyes of 32 ARN patients were collected,and the U-Net method was used to construct the AI algorithm.Thereby,a novel algorithm based on deep machine learning in detection and evaluation of retinal necrosis was constructed for the first time.This algorithm had an area under the receiver operating curve of 0.92,with 86%sensitivity and 88%specificity in the detection of retinal necrosis.For the purpose of retinal necrosis evaluation,necrotic areas calculated by the AI algorithm were significantly positively correlated with viral load in aqueous humor samples(R2=0.7444,P<0.0001)and therapeutic response of ARN(R2=0.999,P<0.0001).Therefore,our AI algorithm has a potential application in the clinical aided diagnosis of ARN,evaluation of ARN severity,and treatment response monitoring.
